R Notebook

hotel_stays %>% plot_bar(maxcat = 50, nrow = 3)

4 columns ignored with more than 50 categories.
country: 166 categories
agent: 315 categories
company: 332 categories
reservation_status_date: 805 categories

skim(hotel_stays)

── Data Summary ────────────────────────
                           Values     
Name                       hotel_stays
Number of rows             75166      
Number of columns          29         
_______________________               
Column type frequency:                
  character                14         
  Date                     1          
  numeric                  14         
________________________              
Group variables            None       

── Variable type: character ──────────────────────────────────────────────────────────────────────────────────────────────────────
   skim_variable               n_missing complete_rate   min   max empty n_unique whitespace
 1 hotel                               0             1    10    12     0        2          0
 2 arrival_date_month                  0             1     3     9     0       12          0
 3 children                            0             1     4     8     0        2          0
 4 meal                                0             1     2     9     0        5          0
 5 country                             0             1     2     4     0      166          0
 6 market_segment                      0             1     6    13     0        7          0
 7 distribution_channel                0             1     3     9     0        5          0
 8 reserved_room_type                  0             1     1     1     0        9          0
 9 assigned_room_type                  0             1     1     1     0       10          0
10 deposit_type                        0             1    10    10     0        3          0
11 agent                               0             1     1     4     0      315          0
12 company                             0             1     1     4     0      332          0
13 customer_type                       0             1     5    15     0        4          0
14 required_car_parking_spaces         0             1     4     7     0        2          0

── Variable type: Date ───────────────────────────────────────────────────────────────────────────────────────────────────────────
  skim_variable           n_missing complete_rate min        max        median     n_unique
1 reservation_status_date         0             1 2015-07-01 2017-09-14 2016-09-01      805

── Variable type: numeric ────────────────────────────────────────────────────────────────────────────────────────────────────────
   skim_variable                  n_missing complete_rate      mean     sd      p0    p25    p50   p75  p100 hist 
 1 lead_time                              0             1   80.0    91.1      0       9     45     124   737 ▇▂▁▁▁
 2 arrival_date_year                      0             1 2016.      0.703 2015    2016   2016    2017  2017 ▃▁▇▁▆
 3 arrival_date_week_number               0             1   27.1    13.9      1      16     28      38    53 ▆▇▇▇▆
 4 arrival_date_day_of_month              0             1   15.8     8.78     1       8     16      23    31 ▇▇▇▇▆
 5 stays_in_weekend_nights                0             1    0.929   0.993    0       0      1       2    19 ▇▁▁▁▁
 6 stays_in_week_nights                   0             1    2.46    1.92     0       1      2       3    50 ▇▁▁▁▁
 7 adults                                 0             1    1.83    0.510    0       2      2       2     4 ▁▂▇▁▁
 8 is_repeated_guest                      0             1    0.0433  0.204    0       0      0       0     1 ▇▁▁▁▁
 9 previous_cancellations                 0             1    0.0158  0.272    0       0      0       0    13 ▇▁▁▁▁
10 previous_bookings_not_canceled         0             1    0.203   1.81     0       0      0       0    72 ▇▁▁▁▁
11 booking_changes                        0             1    0.293   0.736    0       0      0       0    21 ▇▁▁▁▁
12 days_in_waiting_list                   0             1    1.59   14.8      0       0      0       0   379 ▇▁▁▁▁
13 adr                                    0             1  100.0    49.2     -6.38   67.5   92.5   125   510 ▇▆▁▁▁
14 total_of_special_requests              0             1    0.714   0.834    0       0      1       1     5 ▇▁▁▁▁

막대그래프

막대 그래프

hotel_stays %>%
  mutate(arrival_date_month = factor(arrival_date_month,
    levels = month.name
  )) %>%
  count(hotel, arrival_date_month, children) %>%
  group_by(hotel, children) %>%
  mutate(proportion = n / sum(n)) %>%
  plot_ly(x = ~arrival_date_month , y = ~proportion, color = ~children, type = "bar") %>%
  layout(title = "Occupation Type Group",
         barmode = 'group',
         xaxis = list(title = ""),
         yaxis = list(title = ""))

minimal value for n is 3, returning requested palette with 3 different levels
minimal value for n is 3, returning requested palette with 3 different levels
minimal value for n is 3, returning requested palette with 3 different levels
minimal value for n is 3, returning requested palette with 3 different levels

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